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updated 7 months ago

Perceptron by Iftekhar Tanveer

Demo of perceptron learning process (perceptron)

perceptron.m

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updated 10 months ago

Single Perceptron Learning by Suraj Kamya

Without using inbuilt functions from NN Tool. Perceptron learning is implemented. (neural networks, logical gates, perceptron learning)

T=evalnet(P,w,b)

[w,b]=perceplearn(P,t,w,b,ep)

out=hardlimit(in)

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updated 2 years ago

Tutorial de Backpropagation - Un algoritmo de entrenamiento para redes neuronales by Paul Acquatella

Tutorial en Español acerca del algoritmo Backpropagation. Para uso académico y educativo solamente. (redes neuronales, perceptron, entrenamiento)

backpropagation.m

forwardcomp(X,W,L)

setupbackpropagation.m

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updated 3 years ago

A perceptron learns to perform a binary NAND function by fcatak

A perceptron learns to perform a binary NAND function on inputs x0,x1,x2 (artifical intelligenc..., neural networks, perceptron)

PerceptronImpl.m

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updated 3 years ago

Neural Network Simulation of non-linear Mass Spring Damper by Christopher Rouxel

Mass spring damper simulation with non-linear everythings.NN Toolbox not needed (neural network, msd, mass)

B=Bvlin(v)

dampernet=NNdamper()

dampernet=NNdamper_lin()

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updated 3 years ago

SVM Demo by Richard Stapenhurst

An interactive demo of how an SVM works, with comparison to a perceptron (demo, optimization, optimisation)

LinearClassifier

svm_demo

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updated 4 years ago

Rosenblatt's Perceptron by Ibraheem Al-Dhamari

A very simple Neural Networks example. (neural network, perceptron, classification)

MyPerecptronExample

[w,b,pass]=PerecptronTrn(x,y);

e=PerecptronTst(x,y,w,b);

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updated 4 years ago

DeltaRule by Will Dwinnell

Trains a single artificial neuron using the delta rule. (neural, neural net, neural network)

DeltaRule(X,Y,LearningRate,MinimumWeightChange,MaximumPas...

Logistic(Input)

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updated almost 9 years ago

Simple Neural Network by Timothy Felty

A very simple 2 layer neural network (neural network, perceptron, tools)

output=NN2(weights,inputs,af)

tweights=NN2train(IWeights,TDIN,TDOUT,LR,ErTh,AF)

weights=NN2weights(dims)

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